feat(gooddata-sdk): [AUTO] Add ToolCallEventResult schema and toolCallEvents to chat response

packages/gooddata-sdk/src/gooddata_sdk/__init__.py

@@ -274,6 +274,7 @@
 from gooddata_sdk.compute.compute_to_sdk_converter import ComputeToSdkConverter
 from gooddata_sdk.compute.model.attribute import Attribute
 from gooddata_sdk.compute.model.base import ExecModelEntity, ObjId
+from gooddata_sdk.compute.model.chat import ToolCallEventResult
 from gooddata_sdk.compute.model.execution import (
     BareExecutionResponse,
     Execution,

packages/gooddata-sdk/src/gooddata_sdk/compute/model/chat.py

@@ -0,0 +1,32 @@
+# (C) 2026 GoodData Corporation
+from __future__ import annotations
+
+import attrs
+from gooddata_api_client.model.tool_call_event_result import (
+    ToolCallEventResult as ApiToolCallEventResult,
+)
+
+from gooddata_sdk.catalog.base import Base
+
+
+@attrs.define(kw_only=True)
+class ToolCallEventResult(Base):
+    """Represents a tool call event emitted during the agentic loop.
+
+    Only present in :class:`~gooddata_api_client.model.chat_result.ChatResult`
+    when the ``GEN_AI_YIELD_TOOL_CALL_EVENTS`` feature flag is enabled on the
+    GoodData backend.
+    """
+
+    function_arguments: str
+    """JSON-encoded arguments passed to the tool function."""
+
+    function_name: str
+    """Name of the tool function that was called."""
+
+    result: str
+    """Result returned by the tool function."""
+
+    @staticmethod
+    def client_class() -> type[ApiToolCallEventResult]:
+        return ApiToolCallEventResult

packages/gooddata-sdk/tests/compute/test_chat_models.py

@@ -0,0 +1,70 @@
+# (C) 2026 GoodData Corporation
+from __future__ import annotations
+
+import pytest
+from gooddata_sdk.compute.model.chat import ToolCallEventResult
+
+
+@pytest.mark.parametrize(
+    "scenario, input_data, expected_snake",
+    [
+        (
+            "basic",
+            {
+                "functionArguments": '{"x": 1}',
+                "functionName": "get_revenue",
+                "result": "42",
+            },
+            {
+                "function_arguments": '{"x": 1}',
+                "function_name": "get_revenue",
+                "result": "42",
+            },
+        ),
+        (
+            "empty_strings",
+            {
+                "functionArguments": "",
+                "functionName": "noop",
+                "result": "",
+            },
+            {
+                "function_arguments": "",
+                "function_name": "noop",
+                "result": "",
+            },
+        ),
+    ],
+)
+def test_tool_call_event_result_from_dict(scenario, input_data, expected_snake):
+    """Verify ToolCallEventResult round-trips through from_dict / to_dict."""
+    model = ToolCallEventResult.from_dict(input_data)
+
+    assert model.function_arguments == expected_snake["function_arguments"]
+    assert model.function_name == expected_snake["function_name"]
+    assert model.result == expected_snake["result"]
+
+    # Round-trip back to camelCase dict
+    as_dict = model.to_dict(camel_case=True)
+    assert as_dict["functionArguments"] == expected_snake["function_arguments"]
+    assert as_dict["functionName"] == expected_snake["function_name"]
+    assert as_dict["result"] == expected_snake["result"]
+
+
+def test_tool_call_event_result_construction():
+    """Verify direct construction and attribute access."""
+    evt = ToolCallEventResult(
+        function_arguments='{"threshold": 0.5}',
+        function_name="filter_results",
+        result="filtered",
+    )
+    assert evt.function_arguments == '{"threshold": 0.5}'
+    assert evt.function_name == "filter_results"
+    assert evt.result == "filtered"
+
+
+def test_tool_call_event_result_client_class():
+    """Verify client_class() returns the generated API model class."""
+    from gooddata_api_client.model.tool_call_event_result import ToolCallEventResult as ApiToolCallEventResult
+
+    assert ToolCallEventResult.client_class() is ApiToolCallEventResult